Search Results (7,756)

Diabetic encephalopathy affects over 40% of diabetic patients globally, yet effective treatments remain critically limited. This study investigated the synergistic neuroprotective potential of alpha-lipoic acid (ALA) and metformin through the coordinated activation of Nrf2 and AMPK signaling pathways in type 2 diabetes mellitus (T2DM)-induced encephalopathy. Using a clinically relevant streptozotocin-nicotinamide-induced T2DM rat model, sixty male Sprague–Dawley rats were randomly assigned to five groups: control, diabetic, ALA-treated (300 mg/kg), metformin-treated (50 mg/kg), and combination-treated groups over eight weeks. Combination therapy produced statistically validated synergistic effects with significant interaction terms (p < 0.01) across all evaluated parameters. Nuclear Nrf2 translocation increased 3.9-fold and AMPK phosphorylation rose 3.2-fold compared to monotherapies, surpassing mathematical additivity. Mitochondrial function was remarkably restored, with ATP production increasing to 92% of control levels. Cognitive performance was normalized, with spatial memory approaching control values. Combination index analysis (CI < 1.0) confirmed true synergistic interactions across molecular, cellular, and behavioral endpoints. These findings establish a novel convergent mechanism providing compelling evidence for combination ALA–metformin therapy as an innovative treatment strategy for diabetes-associated neurodegeneration. Full article

This study presents a multi-objective optimization framework for designing cylindrical triply periodic minimal surface (TPMS) lattices tailored for bone implant applications. Using an artificial neural network (ANN) as a surrogate model trained on simulated data, four key properties—ultimate stress (U), energy absorption (EA), surface area-to-volume ratio (SA/VR), and relative density (RD)—were predicted from seven lattice design parameters. To address anatomical variability, a novel implant size-based categorization (small, medium, and large) was introduced, and separate optimization runs were conducted for each group. The optimization was performed via the NSGA-II algorithm to maximize mechanical performance (U and EA) and surface efficiency (SA/VR), while filtering for biologically relevant RD values (20–40%). Separate optimization runs were conducted for small, medium, and large implant size groups. A total of 105 Pareto-optimal designs were identified, with 75 designs retained after RD filtering. SHapley Additive exPlanations (SHAP) analysis revealed the dominant influence of thickness and unit cell size on target properties. Kernel density and boxplot comparisons confirmed distinct performance trends across size groups. The framework effectively balances competing design goals and enables the selection of size-specific lattices. The proposed approach provides a reproducible pathway for optimizing bioarchitectures, with the potential to accelerate the development of lattice-based implants in personalized medicine. Full article

This paper explores the complex dynamics of mixed convective flow in a Casson fluid saturated in a non-Darcy porous medium, focusing on the influence of gyrotactic microorganisms, internal heat generation, and multiple convective mechanisms. Casson fluids, known for their non-Newtonian behavior, are relevant in various industrial and biological contexts where traditional fluid models are insufficient. This study addresses the limitations of the standard Darcy’s law by examining non-Darcy flow, which accounts for nonlinear inertial effects in porous media. The governing equations, derived from conservation laws, are transformed into a system of no linear ordinary differential equations (ODEs) using similarity transformations. These ODEs are solved numerically using a finite differencing method that incorporates central differencing, tridiagonal matrix manipulation, and iterative procedures to ensure accuracy across various convective regimes. The reliability of this method is confirmed through validation with the MATLAB (R2024b) bvp4c scheme. The investigation analyzes the impact of key parameters (such as the Casson fluid parameter, Darcy number, Biot numbers, and heat generation) on velocity, temperature, and microorganism concentration profiles. This study reveals that the Casson fluid parameter significantly improves the velocity, concentration, and motile microorganism profiles while decreasing the temperature profile. Additionally, the Biot number is shown to considerably increase the concentration and dispersion of motile microorganisms, as well as the heat transfer rate. The findings provide valuable insights into non-Newtonian fluid behavior in porous environments, with applications in bioengineering, environmental remediation, and energy systems, such as bioreactor design and geothermal energy extraction. Full article

We present a numerical investigation comparing two entanglement generation protocols in finite XX spin chains with varying spin magnitudes ($s=1/2,1,3/2$). Protocol 1 (P1) relies on staggered couplings to steer correlations toward the ends of the chain. At the same time, Protocol 2 (P2) adopts a dual-port architecture that uses optimized boundary fields to mediate virtual excitations between terminal spins. Our results show that P2 consistently outperforms P1 in all spin values, generating higher-fidelity entanglement in shorter timescales when evaluated under the same system parameters. Furthermore, P2 exhibits superior robustness under realistic imperfections, including diagonal and off-diagonal disorder, as well as dephasing noise. To further assess the resilience of both protocols in experimentally relevant settings, we employ the pseudomode formalism to characterize the impact of non-Markovian noise on the entanglement dynamics. Our analysis reveals that the dual-port mechanism (P2) remains effective even when memory effects are present, as it reduces the excitation of bulk modes that would otherwise enhance environment-induced backflow. Together, the scalability, efficiency, and noise resilience of the dual-port approach position it as a promising framework for entanglement distribution in solid-state quantum information platforms. Full article

Background/Objectives: Developmental dysplasia of the hip (DDH) affects 1–3% of newborns and requires early detection for optimal outcomes. DDH involves abnormal acetabular–femoral congruence between the acetabulum and femoral head, resulting from either shallow acetabular development or delayed femoral ossification of the femoral head. We evaluated the ossification nucleus of the femoral head (ONFH) to determine prevalence, radiographic timing, and associations with perinatal factors. Methods: We analyzed 100 pelvic radiographs of infants between 90 and 150 days of age. Participants were selected by convenience sampling, based on inclusion criteria. We identified the presence of ONFH and measured biometric parameters, morphology, and anatomical location. Sociodemographic and perinatal data were collected from the participating infants. Results: The prevalence of ONFH was 33%, and the mean age at visualization was 104 days. The presence of ONFH was correlated with birth weight (p = 0.011), discharge weight (p = 0.005), and weight at 1 month (p = 0.034). In our study, female sex (p = 0.004) was associated with a 4.966-fold higher odds of ONFH prevalence compared to males. Conclusions: This study provides relevant evidence regarding the prevalence, morphology, and characteristics of ONFH. Few studies report this information on ONFH in different populations. The optimal timing for radiographic visualization of ONFH in infants remains undefined, but the appearance of the ONFH was concentrated around 104 days of life. The novel association between weight and ONFH provides new insights into DDH. This provides new insights for DDH screening. This association warrants further research for the early detection of DDH. Full article

Remote reefs offer insights into natural coral dynamics, influenced by regional environmental factors and climate change fluctuations. Clipperton Atoll is the eastern tropical Pacific’s most isolated reef, where coral reef growth and life strategies have been poorly studied so far. Recognizing the coral species’ growth response might help understand ecological dynamics and the impacts of anthropogenic stressors on coastal reefs. The present study evaluates annual coral growth parameters of the most abundant coral reef-building species, Porites australiensis, Porites arnaudi, Porites lutea, and Porites lobata. The results showed that during 2015–2019, corals exhibited the lowest annual linear extension (0.65 ± 0.29 cm yr⁻¹), skeletal density (1.14 ± 0.32 g cm⁻³), and calcification rates (0.78 ± 0.44 g cm⁻² yr⁻¹) for the genera along the Pacific. Differences in growth patterns among species were observed, with Porites lutea and Porites lobata showing a higher radial extension, developing massive-hemispherical morphologies, and acting as structural stabilizers; meanwhile, P. arnaudi and P. australiensis exhibited more skeletal compaction but also with a high plasticity on their morphologies, contributing to benthic heterogeneity. These differences are particularly important as each species fulfills different ecological functions within the reef, contributing to the ecosystem balance and enhancing the relevance of the massive species in the physical structure of remote reef systems, such as Clipperton Atoll. Full article

The human exposome, including dietary exposures such as pesticides, additives, and environmental contaminants, plays a critical role in shaping the gut microbiota (GM) and long-term health outcomes. While the Mediterranean Diet is known for its health-promoting effects, the role of food quality, specifically organic vs. conventional products, in modulating GM within this dietary pattern remains underexplored. The aim of this study was to evaluate (1) whether an Italian Mediterranean Organic Diet (IMOD) confers additional benefits compared to an Italian Mediterranean non-Organic Diet (IMnOD), and (2) the impact of IMOD and IMnOD versus a free diet (No Diet) on GM and anthropometric parameters. A randomized, controlled trial was conducted on 39 healthy subjects. Eligible subjects were divided into the following groups: (1) 4 weeks No Diet, (2) 4 weeks IMOD, and (3) 4 weeks IMnOD. Microbiota profiling (16S rRNA sequencing), body composition (BIA), and dietary adherence (MEDAS, FFQ) were evaluated. Distinct microbial shifts following both IMOD and IMnOD compared to No Diet were revealed. Several taxa previously associated with short-chain fatty acid (SCFA) biosynthesis (i.e., Anaerobutyricum hallii, Anaerostipes hadrus, and Dorea longicatena) were increased after both Mediterranean Diet interventions, while Parabacteroides distasonis showed a specific increase in the IMOD group. No significant changes in body weight or composition were observed. These findings suggest that adherence to a Mediterranean Diet, regardless of food source, reshapes the gut microbiota, while organic food intake may influence specific microbial trajectories. Our results support the relevance of food quality in dietary interventions. Full article

The prevention of bubble coalescence is essential in various industrial processes, such as mineral flotation, where the stability of air–liquid interfaces significantly affects performance. The combined influence of multiple physicochemical parameters on bubble coalescence remains insufficiently understood, particularly under conditions relevant to flotation. This study explores the key factors that influence the inhibition of bubble coalescence in aqueous solutions containing methyl isobutyl carbinol (MIBC), providing a systematic comparative analysis to assess the effect of each variable on coalescence inhibition. An experimental method was employed in which two air bubbles were formed from identical capillaries and brought into contact either head-to-head or side-by-side, then held until coalescence occurred. This setup allows for reliable measurements of coalescence time with minimal variability regarding the conditions under which the bubbles interact. The study examined the effects of several factors: temperature, pH, salt concentration and type, bubble approach speed, contact area, and contact configuration. The results reveal that coalescence is delayed at lower temperatures, alkaline pH conditions, high salt concentrations, and larger interfacial contact areas between bubbles. Within the range studied, the influence of approach speed was found to be insignificant. These findings provide valuable insights into the fundamental mechanisms governing bubble coalescence and offer practical guidance for optimizing industrial processes that rely on the controlled stabilization of air–liquid interfaces. By understanding and manipulating the factors that inhibit coalescence, it is possible to design more efficient and sustainable mineral flotation systems, thereby reducing environmental impact and conserving water resources. Full article

Precisely predicting photovoltaic (PV) output is crucial for reliable grid integration; so far, most models rely on site-specific sensor data or treat large meteorological datasets as black boxes. This study proposes an explainable machine-learning framework that simultaneously ranks the most informative weather parameters and reveals their physical relevance to PV generation. Starting from 27 local and plant-level variables recorded at 15 min resolution for a 1 MW array in Çanakkale region, Türkiye (1 August 2022–3 August 2024), we apply a three-stage feature-selection pipeline: (i) variance filtering, (ii) hierarchical correlation clustering with Ward linkage, and (iii) a meta-heuristic optimizer that maximizes a neural-network R² while penalizing poor or redundant inputs. The resulting subset, dominated by apparent temperature and diffuse, direct, global-tilted, and terrestrial irradiance, reduces dimensionality without significantly degrading accuracy. Feature importance is then quantified through two complementary aspects: (a) tree-based permutation scores extracted from a set of ensemble models and (b) information gain computed over random feature combinations. Both views converge on shortwave, direct, and global-tilted irradiance as the primary drivers of active power. Using only the selected features, the best model attains an average R² ≅ 0.91 on unseen data. By utilizing transparent feature-reduction techniques and explainable importance metrics, the proposed approach delivers compact, more generalized, and reliable PV forecasts that generalize to sites lacking embedded sensor networks, and it provides actionable insights for plant siting, sensor prioritization, and grid-operation strategies. Full article

As populations age and workforces decline, the need for accessible health assessment methods grows. The merging of accessible and affordable sensors such as inertial measurement units (IMUs) and advanced machine learning techniques now enables gait assessment beyond traditional laboratory settings. A total of 52 participants walked at three speeds while carrying a smartphone-sized IMU in natural positions (hand, trouser pocket, or jacket pocket). A previously trained Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM)-based machine learning model predicted gait events, which were then used to calculate stride time, stance time, swing time, and double support time. Stride time predictions were highly accurate (<5% error), while stance and swing times exhibited moderate variability and double support time showed the highest errors (>20%). Despite these variations, moderate-to-strong correlations between the predicted and experimental spatiotemporal gait parameters suggest the feasibility of IMU-based gait tracking in real-world settings. These associations preserved inter-subject patterns that are relevant for detecting gait disorders. Our study demonstrated the feasibility of extracting clinically relevant gait parameters using IMU data mimicking smartphone use, especially parameters with longer durations such as stride time. Robustness across sensor locations and walking speeds supports deep learning on single-IMU data as a viable tool for remote gait monitoring. Full article

Differential Object Marking (DOM) is a cross-linguistic phenomenon in which the overt marking of direct objects of certain transitive verbs exhibits distinct morpho-syntactic properties. In Turkish, DOM is realized by the accusative suffix -(y)I and is considered to be determined by parameters such as referentiality/specificity, affectedness, and topicality. In addition, Enç argues that discourse-linking, which is a backward-looking discourse function, is another relevant parameter. In this paper, we investigate whether DOM also serves a forward-looking discourse function, which has remained underexplored. Using corpus studies and offline experiments, we investigate the forward discourse function of DOM in Turkish by analyzing the frequency of anaphoric expressions referring to the direct object with vs. without DOM. Corpus data show that non-modified human indefinite direct objects with DOM are taken up significantly more often in the subsequent discourse than those without DOM. However, forced-choice and paragraph continuation tasks do not support these observations. We evaluate various parameters that might contribute to the discourse prominence of direct objects with DOM and those that might mask such effects. We conclude that there is some corpus evidence that DOM contributes to a forward-looking discourse function, though our experimental methods may be inadequate to capture it. Full article

This study analyzes the recent scientific literature on advanced biocompatible materials for triboelectric nanogenerators (TENGs) in biomedical applications. Focusing on materials like synthetic polymers, carbon-based derivatives, and advanced hybrids, the study interprets findings regarding their triboelectric properties and performance influenced by surface texture and additive manufacturing techniques. Major findings reveal that precise control over surface morphology, enabled by additive manufacturing (AM) is promising for optimizing transferred charge density and maximizing TENG efficiency. The analysis highlights the relevance of these material systems and fabrication strategies for developing self-powered wearable and implantable biomedical devices through enabling biocompatible energy-harvesting components that can operate autonomously without external power, underscoring the need for stringent biocompatibility and performance stability. This work synthesizes current progress, identifying critical material and process design parameters for advancing the field of biocompatible TENGs. Full article

Biophilic design has emerged as a multidimensional response to growing concerns about health, well-being, and ecological balance in the built environment. Despite its rising prominence, research on the topic remains fragmented across building typologies, user groups, and geographic contexts. This study presents a comprehensive review of the biophilic design literature, employing a hybrid methodology combining structured content analysis and bibliometric mapping. All peer-reviewed studies indexed in the Web of Science and Scopus were manually screened for architectural relevance and systematically coded. A total of 435 studies were analysed to identify key trends, thematic patterns, and research gaps in the biophilic design discipline. This review categorises the literature by methodological strategies, building typologies, spatial scales, population groups, and specific biophilic design parameters. It also examines geographic and cultural dimensions, including climate responsiveness, heritage buildings, policy frameworks, theory development, pedagogy, and COVID-19-related research. The findings show a strong emphasis on institutional contexts, particularly workplaces, schools, and healthcare, and a reliance on perception-based methods such as surveys and experiments. In contrast, advanced tools like artificial intelligence, simulation, and VR are notably underused. Few studies engage with neuroarchitecture or neuroscience-informed approaches, despite growing recognition of how spatial design can influence cognitive and emotional responses. Experimental and biometric methods remain scarce among the few relevant contributions, revealing a missed opportunity to connect biophilic strategies with empirical evidence. Regarding biophilic parameters, greenery, daylight, and sensory experience are the most studied parameters, while psychological parameters remain underexplored. Cultural and climate-specific considerations appear in relatively few studies, and many fail to define a user group or building typology. This review highlights the need for more inclusive, context-responsive, and methodologically diverse research. By bridging macro-scale bibliometric patterns with fine-grained thematic insights, this study provides a replicable review model and valuable reference for advancing biophilic design as an evidence-based, adaptable, and human-centred approach to sustainable architecture. Full article

Background/Objectives: Complications of edentulism include bone resorption, muscular dysfunction, temporomandibular joint disorders (TMJ), and stomatognathic system dysfunctional syndrome (SSDS). The objectives of the study were as follows: to analyze the distribution of edentulism complications related to sociodemographic and clinical parameters and to quantify the strength of relationships between edentulism complications and these socio-demographic or clinical variables. Materials and Methods: This cross-sectional study investigated 150 edentulous subjects (mean age 61.54 +/− 8.99 years) scheduled for hybrid prosthetic therapy. The distribution of edentulism complications was assessed in relation to sex-specific and age-specific patterns, edentulism location (maxillary vs. mandibular), edentulism extension (partial reduced, partial extended, subtotal, complete edentulism), and Kennedy classification (class I vs. class II vs. class IV). Cramér’s V was used to measure the strength of the association between edentulism complications and sociodemographic and clinical factors. Results: The most prevalent complications were more frequent in males—bone resorption (74.2% vs. 40.9%), malocclusion (97.5% vs. 84.9%), TMJ disorders (74.2% vs. 57.0%), muscular disorders (62.5% vs. 31.2%), dyshomeostasis (64.2% vs. 31.2%), and SSDS (79.2% vs. 53.8%). The most relevant associations were found between age group and clinical variables such as irregular ridge (Cramer’s V = 0.737), long/thick frenum (0.711), and SSDS (0.544), while edentulism category was strongly associated with irregular ridge (0.585), TMJ disorders (0.493), and bone resorption (0.492). Conclusions: The type and stage of edentulism emerged as key determinants of complication severity, with complete and subtotal edentulism being associated with the highest rates of muscular and temporomandibular joint dysfunctions. Full article

This study explores the optimisation of nozzle design for external twin fluid, single-stage atomisation in handling high-viscosity, shear-thinning polydimethylsiloxane (PDMS). A single PDMS grade was employed and atomised using unheated sonic air and the viscosity was varied by the fluid temperature. A systematic experimental approach was used, varying nozzle geometry—specifically apex angle, gas nozzle diameter, and number of gas nozzles—to identify the optimal nozzle configuration (ONC). The spray qualities of the nozzle configurations were evaluated via high-speed imaging at 75,000 FPS. Shadowgraphy was employed for the optical characterisation of the spray, determining the optimal volumetric air-to-liquid ratio (ALR), a key parameter influencing energy efficiency and operational cost, and for assessing droplet size distributions under varying ALR and viscosity of PDMS. The ONC yielded a Sauter mean diameter $d_{32}$ of 570 × 10⁻⁶$\mathrm{m}$, at an ALR of 8532 and a zero-shear viscosity of 15.9 $\mathrm{Pa}$ $\mathrm{s}$. The results are relevant for researchers and engineers developing twin fluid atomisation systems for challenging industrial fluids with similar physical properties, such as those in wastewater treatment and coal–water slurry atomisation (CWS). This study provides design guidelines for external twin fluid atomisers to enhance atomisation efficiency under such conditions. Full article